• The Journal of the Acoustical Society of Korea
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• 제39권5호
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• pp.461-467
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• 2020

In noisy and multi-speaker environments, the performance of speech recognition is unavoidably lower than in a clean environment. To improve speech recognition, in this paper, the signal of the speaker of interest is extracted from the mixed speech signals with multiple speakers. The VoiceFilter model is used to effectively separate overlapped speech signals. In this work, clustering by Probabilistic Linear Discriminant Analysis (PLDA) similarity score was employed to detect the speech signal of the interested speaker, which is used as the reference speaker to VoiceFilter-based separation. Therefore, by utilizing the speaker feature extracted from the detected speech by the proposed clustering method, this paper propose a speaker diarization system using only the mixed speech without an explicit reference speaker signal. We use phone-dataset consisting of two speakers to evaluate the performance of the speaker diarization system. Source to Distortion Ratio (SDR) of the operator (Rx) speech and customer speech (Tx) are 5.22 dB and -5.22 dB respectively before separation, and the results of the proposed separation system show 11.26 dB and 8.53 dB respectively.

• Safety and Health at Work
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• 제10권4호
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

• IEMEK Journal of Embedded Systems and Applications
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• 제13권1호
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• pp.17-24
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• 2018

Military camera equipment has a problem that observability is inferior due to various shaking factors. In this paper, we propose an image stabilization algorithm considering performance and execution time to solve this problem and implemented it in Zynq SoC. We stabilized both the simple shaking in the fixed observation position and the sudden shaking in the moving observation position. The feature of the input image is extracted by the Sobel edge algorithm, the subblock with the large edge data is selected, and the motion vector, which is the compensation reference, is calculated through template matching using the 3-step search algorithm of the region of interest. In addition, the proposed algorithm can distinguish the shaking caused by the simple shaking and the movement by using the Kalman filter, and the stabilized image can be obtained by minimizing the loss of image information. To demonstrate the effectiveness of the proposed algorithm, experiments on various images were performed. In comparison, PSNR is improved in the range of 2.6725~3.1629 (dB) and image loss is reduced from 41% to 15%. On the other hand, we implemented the hardware-software integrated design using HLS of Xilinx SDSoC tool and confirmed that it operates at 32 fps on the Zynq board, and realized SoC that operates with real-time processing.

• Proceedings of the Korea Contents Association Conference
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• 한국콘텐츠학회 2006년도 추계 종합학술대회 논문집
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• pp.47-51
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• 2006

As the recent announcement of the functional cosmetics law, the need of studies on efficacy evaluation of skin related cosmetics and medical supplies has grown. Especially to identify skin improvement, we have to compare the exact parts of the skin, however up to now it is compared only by image matching that is appeared to the human eye. This study proposes the automatical image matching system for improving the accuracy of evaluation a skin improvement. Firstly we define the feature of the skin pores and wrinkles, and extract anticipation region from skin images. And then, we calculate moments for each extracted regions and classify them as pores and wrinkles. After that, we calculate the vector by computing centroids between each regions. Through this process, we compare the vector similarities and perform the matching between existing image and reference image. To verify the efficiency of the algorithm several experiments are conducted.

• Journal of Electrical Engineering and Technology
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• 제2권4호
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• pp.468-477
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• 2007

The DTC of voltage source inverter-fed PMSMs is based on hysteresis controllers of torque and flux. It has several advantages, namely, elimination of the mandatory rotor position sensor, less computation time, and rapid torque response. In addition, the stator resistance is the only parameter, which should be known, and no reference frame transformation is required. The DTC theory has achieved great success in the control of induction motors. However, for the control of PMSM drives proposed a few years ago, there are many basic theoretical problems that must be clarified. This paper describes an investigation into the effect of the zero voltage space vectors in the DTC system and points out that if using it rationally, not only can the DTC of the PMSM drive be driven successfully, but torque and flux ripples are reduced and overall performance of the system is improved. The implementation of DTC in PMSM drives is described and the switching tables specific for an interior PMSM are derived. The conventional eight voltage-vector switching table, which is namely used in the DTC of induction motors does not seem to regulate the torque and stator flux in a PMSM well when the motor operates at low speed. Modelling and simulation studies have both revealed that a six voltage-vector switching table is more appropriate for PMSM drives at low speed. In addition, the sources of difficulties, namely, the error in the detection of the initial rotor position, the variation of stator resistance, and the offsets in measurements are analysed and discussed.

• Horticultural Science & Technology
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• 제28권4호
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• pp.672-677
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• 2010

A duplex PCR method was developed to detect a transformation vector pSPB130 used in the development of a genetically modified (GM) rose plant. To detect a GM rose plant, the anthocyanin synthase ($ANS$) was used as an endogenous reference gene of rose in PCR detection. The primer pair RHANS-KF/KR producing 107 bp amplicon was used to amplify the $ANS$ gene and no amplified product was observed in any of the 9 different plants used as a template. The primer pair GMRH-KF/KR was designed to amplify the junction sequence between 35S promoter and flavonoid 3',5'-hydroxylase ($F3^{\prime}5^{\prime}H$) gene in pSPB130. The detection limit of the duplex PCR method is approximately 0.5%. This result indicates that this duplex PCR method could be useful for monitoring unauthorized GM rose in Korea.

• Journal of the Institute of Electronics Engineers of Korea SC
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• 제48권3호
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• pp.6-12
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• 2011

Electric vehicles and robots are real-time distributed control systems composed of multiple drive subsystems using micro controller units. Each control subsystem should be modular, compact, power saving, interoperable and fault tolerable in order to be incorporated into the networked real-time distributed control system. Under the networked real-time distributed control the synchronization problem can be occurred to the position and orientation tracking control due to the load variance, mismatch and time delay between the multiple drive subsystems. This paper suggests two types of position synchronization control of the single link manipulators. One of them is composed of cross controller, Kalman filter and disturbance observer, and the other uses the generation of target trajectories to minimize the gradient vector of the scalar function which is composed of the sum of square errors between the reference input vector and the output vectors. The availability of the proposed control schemes is shown through the control experiments.

• Journal of Broadcast Engineering
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• 제21권4호
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• pp.578-591
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• 2016

In this paper, the fast encoding algorithm in High Efficiency Video Coding (HEVC) encoder was studied. For the encoding efficiency, the current HEVC reference software is divided the input image into Coding Tree Unit (CTU). then, it should be re-divided into CU up to maximum depth in form of quad-tree for RDO (Rate-Distortion Optimization) in encoding precess. But, it is one of the reason why complexity is high in the encoding precess. In this paper, to reduce the high complexity in the encoding process, it proposed the method by determining the maximum depth of the CU using a hierarchical clustering at the pre-processing. The hierarchical clustering results represented an average combination of motion vectors (MV) on neighboring blocks. Experimental results showed that the proposed method could achieve an average of 16% time saving with minimal BD-rate loss at 1080p video resolution. When combined the previous fast algorithm, the proposed method could achieve an average 45.13% time saving with 1.84% BD-rate loss.

• Journal of the Korea Society for Simulation
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• 제21권2호
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• pp.79-90
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• 2012

In this paper, a feature signal extraction method is proposed in order to enhance the low performance of fault detection caused by unbalanced data which denotes the situations when severe disparity exists between the numbers of class instances. Most of the cyclic signals gathered during the process are recognized as normal, while only a few signals are regarded as fault; the majorities of cyclic signals data are unbalanced data. SOM(Self-Organizing Map)-based feature signal extraction method is considered to fix the adverse effects caused by unbalanced data. The weight neurons, mapped to the every node of SOM grid, are extracted as the feature signals of both class data which are used as a reference data set for fault detection. kNN(k-Nearest Neighbor) and SVM(Support Vector Machine) are considered to make fault detection models with comparisons to Hotelling's $T^2$ Control Chart, the most widely used method for fault detection. Experiments are conducted by using simulated process signals which resembles the frequent cyclic signals in semiconductor manufacturing.

• 한국환경농학회:학술대회논문집
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• 한국환경농학회 2009년도 정기총회 및 국제심포지엄
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• pp.228-239
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• 2009

The observations on climate change show a clear increase in the temperature of the Earth's surface and the oceans, a reduction in the land snow cover, and melting of the sea ice and glaciers. The effects of climate change are likely to include more variable weather, heat waves, increased mean temperature, rains, flooding and droughts. The threat of climate change and global warming on human and animal health is now recognized as a global issue. This presentation is described an overview of the latest scientific knowledge on the impact of climate change on zoonotic diseases. Climate strongly affects agriculture and livestock production and influences animal diseases, vectors and pathogens, and their habitat. Global warming are likely to change the temporal and geographical distribution of infectious diseases, including those that are vector-borne such as West Nile fever, Rift Valley fever, Japanese encephalitis, bluetongue, malaria and visceral leishmaniasis, and other diarrheal diseases. The distribution and prevalence of vector-borne diseases may be the most significant effect of climate change. The impact of climate change on the emergence and re-emergence of animal diseases has been confirmed by a majority of countries. Emerging zoonotic diseases are increasingly recognized as a global and regional issue with potential serious human health and economic impacts and their current upward trends are likely to continue. Coordinated international responses are therefore essential across veterinary and human health sectors, regions and countries to control and prevent emerging zoonoses. A new early warning and alert systems is developing and introducing for enhancing surveillance and response to zoonotic diseases. And international networks that include public health, research, medical and veterinary laboratories working with zoonotic pathogens should be established and strengthened. Facing this challenging future, the long-term strategies for zoonotic diseases that may be affected by climate change is need for better prevention and control measures in susceptible livestock, wildlife and vectors in Korea. In conclusion, strengthening global, regional and national early warning systems is extremely important, as are coordinated research programmes and subsequent prevention and control measures, and need for the global surveillance network essential for early detection of zoonotic diseases.